Abstract
Emerging antibiotic resistant bacteria constitute one of the biggest threats to public health. Surface-enhanced Raman scattering (SERS) is highly promising for detecting such bacteria and for antibiotic susceptibility testing (AST). SERS is fast, non-destructive (can probe living cells) and it is technologically flexible (readily integrated with robotics and machine learning algorithms). However, in order to integrate into efficient point-of-care (PoC) devices and to effectively replace the current culture-based methods, it needs to overcome the challenges of reliability, cost and complexity. Recently, significant progress has been made with the emergence of both new questions and new promising directions of research and technological development. This article brings together insights from several representative SERS-based AST studies and approaches oriented towards clinical PoC biosensing. It aims to serve as a reference source that can guide progress towards PoC routines for identifying antibiotic resistant pathogens. In turn, such identification would help to trace the origin of sporadic infections, in order to prevent outbreaks and to design effective medical treatment and preventive procedures.
| Original language | English |
|---|---|
| Article number | 114843 |
| Journal | Biosensors and Bioelectronics |
| Volume | 219 |
| Early online date | 25 Oct 2022 |
| DOIs | |
| Publication status | Published - 31 Jan 2023 |
Funding
N.E. Dina acknowledges the financial support provided by the Ministry of Research, Innovation and Digitization, project number PN-III-P1-1.1-TE-2019-0910 and the Subprogramme 1.2 - Institutional Performance - Funding Projects for Excellence in RDI , Contract No. 37PFE/30.12.2021 , within PNCDI III . V.K.V. acknowledges support from the Royal Society through the University Research Fellowships and the Royal Society grant RGF\EA\180228 , as well as the EPSRC grant EP /T001046/1. V.K.V and L.Z. acknowledge the International Collaboration Awards 2020 of the Royal Society (No. ICA\R1\201088 ). Imran Amin and Sadia Z. Bajwa are thankful to the Higher Education Commission of Pakistan for funding via Grant No. 6117 . Raman spectroscopy allows the identification of specific molecular vibrations and can assign their distinguished and unique signals. It also has the potential to identify the microbial species at strain level and their antibiotic resistance, in combination with confocal spectroscopy. In Raman fingerprinting, different bacterial phenotypes exhibit subtle differences in their corresponding Raman spectra owing to their unique molecular composition. A promising phenotypic method for determining the pathogenicity was implemented by J. Popp et al. by means of Raman microspectroscopy and a principal component analysis (PCA) - support vector machines (SVM)-based model, trained for fast screening of single bacterial cells (Lorenz et al., 2020; Nakar et al., 2022). The authors took measures to avoid misinterpretation of strain identification to pathogenicity by using increased strain variety for the classifier and enhanced sensitivity (by defining a majority vote of multiple spectra). The majority vote method is based on the presumption that only one bacterial species is present in majority in the sample. Thus, a combination of multiple spectra (7 spectra instead of only 3 or 5 spectra) was used to generate a prediction by the trained SVM model. This way, an increased mean sensitivity of up to 95% in identifying clinical isolates as pathogenic strains was obtained by applying the leave-one-batch-out cross-validation.Pathogens can now be individually identified with SERS, without labelling or specific receptor usage, such as antibodies (Tahir et al., 2020). In an ideal approach, a semi-quantitative detection of bioanalytes or microorganisms should be possible from a single droplet deposited onto a designed detection platform (Witkowska et al., 2021). Most recently, a self-supporting liquid film (SLF) SERS platform was developed by Liu et al. as detection and therapeutic drug monitoring (TDM) platform for PoC testing of biofluids (Fig. 6) (Liu et al., 2021).The quantitative analysis provided by SERS-AST method is a key aspect to be achieved with similar sensitivity as for other FDA approved methods before its translation into clinical routine testing. Successful quantitative analyses for SERS-AST are discussed by recent studies and support the potential of assessing such determination even in real-time. A semi-quantitative SERS-based rapid medical diagnostics for periodontitis was developed for saliva samples analysis and discerning between oral pathogens with different implications for the patient (Witkowska et al., 2021). The analysis of a microdroplet of sample is assessed by mixing within a microfluidic chip with magnetic NPs and sequential separation of microbial cells by magnetic forces for their laser irradiation and identification. By monitoring in real-time the spectral signatures of the pathogens, particularly the intensity for specific bands found at 732 and 1331 cm−1, a calibration for bacteria concentration ranging in between 108 – 102 cfu/ml was performed.N.E. Dina acknowledges the financial support provided by the Ministry of Research, Innovation and Digitization, project number PN-III-P1-1.1-TE-2019-0910 and the Subprogramme 1.2 - Institutional Performance - Funding Projects for Excellence in RDI, Contract No. 37PFE/30.12.2021, within PNCDI III. V.K.V. acknowledges support from the Royal Society through the University Research Fellowships and the Royal Society grant RGF\EA\180228, as well as the EPSRC grant EP/T001046/1. V.K.V and L.Z. acknowledge the International Collaboration Awards 2020 of the Royal Society (No. ICA\R1\201088). Imran Amin and Sadia Z. Bajwa are thankful to the Higher Education Commission of Pakistan for funding via Grant No. 6117.
| Funders | Funder number |
|---|---|
| Race and Difference Initiative, Emory University | 37PFE/30.12.2021 |
| Race and Difference Initiative, Emory University | |
| Ministerul Cercetării, Inovării şi Digitalizării | PN-III-P1-1.1-TE-2019-0910 |
| Ministerul Cercetării, Inovării şi Digitalizării | |
| Engineering and Physical Sciences Research Council | ICA\R1\201088, EP /T001046/1 |
| Engineering and Physical Sciences Research Council | |
| Royal Society | RGF\EA\180228 |
| Royal Society | |
| Higher Education Commision, Pakistan | 6117 |
| Higher Education Commision, Pakistan |
Keywords
- Antibiotic susceptibility test
- Clinical diagnosis
- Multidrug resistant pathogens
- PoC biosensing
- SERS
- SERS-based biosensors
ASJC Scopus subject areas
- Biotechnology
- Biophysics
- Biomedical Engineering
- Electrochemistry
